State estimation for stochastic object on the base of modeling trend in time series
Prikladnaâ diskretnaâ matematika, no. 12 (2010), pp. 103-105
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A new model for state recognition in dynamic object provided in the form of non-stationary time series is discussed. Algorithms for construction of generalized etalons of dynamic object state and of modeling segment of time series on the base of generalized etalons and difference scheme are suggested. Availability of the model is shown on an applied problem.
@article{PDM_2010_12_a53,
author = {S. I. Kolesnikova and A. A. Belous},
title = {State estimation for stochastic object on the base of modeling trend in time series},
journal = {Prikladna\^a diskretna\^a matematika},
pages = {103--105},
publisher = {mathdoc},
number = {12},
year = {2010},
language = {ru},
url = {http://geodesic.mathdoc.fr/item/PDM_2010_12_a53/}
}
TY - JOUR AU - S. I. Kolesnikova AU - A. A. Belous TI - State estimation for stochastic object on the base of modeling trend in time series JO - Prikladnaâ diskretnaâ matematika PY - 2010 SP - 103 EP - 105 IS - 12 PB - mathdoc UR - http://geodesic.mathdoc.fr/item/PDM_2010_12_a53/ LA - ru ID - PDM_2010_12_a53 ER -
S. I. Kolesnikova; A. A. Belous. State estimation for stochastic object on the base of modeling trend in time series. Prikladnaâ diskretnaâ matematika, no. 12 (2010), pp. 103-105. http://geodesic.mathdoc.fr/item/PDM_2010_12_a53/